The overarching goal of this research is to achieve a better understanding of how variation of genetically encoded physical chemical properties of proteins affects phenotypic changes of simple bacterial organisms. Specifically, here we focus on the investigation of the impact of non-functional, spurious protein-protein interactions (NF-PPI) caused by mutations in crowded cellular environment on phenotypic variation and fitness of model organisms in silico and in vivo in E. coli cells. This is a multi-tool multiscale research, which synthesizes theoretical and experimental approaches to achieve its Specific Aims. The theoretical approaches are based on multiscale models of increasing complexity where cytoplasm of model cells is presented in a Biophysically realistic manner, and fitness of model organisms is determined by sequence-dependent folding and functional interactions of model proteins. The latter are expressed at certain concentrations in cytoplasm of model cells and are subject to Protein Quality Control (PQC). A related experimentation aims at testing and improving the main assumptions of theoretical models. The experimental approach is bottom up and is based on rational genome editing whereby mutations of interest in ORF of essential proteins are introduced directly on E. coli chromosome. The effect of mutations on Biophysical and Biochemical properties of affected proteins is simultaneously evaluated in vitro and phenotypic and fitness effect is determined in vivo for strains in which same mutations are chromosomally incorporated. The problems that are being addressed in this research are: 1) To what extent do destabilizing mutations in metabolic enzymes give rise to NF-PPI. 2) How much do NF- PPI contribute to fitness and phenotypic effects of mutations and how distinguishable is that from self- association (aggregation). 3) How do active components of PQC - chaperonins and proteases - mitigate potentially detrimental effect of NF-PPI on bacterial fitness? Overall this research will significantly advance our understanding of physical chemical factors that determine fitness landscape of bacterial organisms providing a better description of molecular evolution of their proteomes and the dynamics of their response to treatment in clinical environment.